The present invention relates to a method and apparatus for the automatic detection of udder diseases, such as mastitis, in dairy animals.
Early detection and ongoing monitoring of the health and welfare of dairy animals is imperative. Individual dairy animals suffering from an udder disease typically produce milk of lower quality and/or quantity. Furthermore, illness spreading throughout a dairy herd can significantly impact the output of the herd as a whole.
For example, mastitis is widely recognised as one of the top three most common and costly health conditions affecting dairy animals, along with lameness and fertility management. Estimates put the cost of mastitis alone to UK dairy farms at more than £160 million per annum and the actual cost may be significantly higher, due to unrecorded or undiagnosed cases.
It is estimated that in herds without effective mastitis control, approximately 40% of dairy animals can be infected in two quarters of the udder.
Mastitis is generally indicated by an increase in somatic cell count (SCC) in the milk. A low level of SCC is used as an indicator of good quality milk and can attract a price premium.
Clinical mastitis will manifest itself through changes in the composition of the milk and inflammation of the udder, which will be visually apparent. As well as the pain and discomfort to the animal, reduced milk yield and quality will result. As the infection worsens, costs are also incurred through vet treatment, discarded milk, increased labour costs and ultimately the culling and replacement of stock.
Due to these costs, mastitis is one of the top three reasons dairy animals are culled.
Even sub-clinical mastitis (i.e. lower levels of infection which may not be visually apparent during routine observations of the dairy animal) can reduce the value of the milk.
If diagnosed early, then self-healing is possible with simple hygiene routines, however this may not be possible by the time the disease has progressed far enough to be detected by visual inspection.
Known early mastitis detection methods are either labour intensive or expensive to automate. For example, the condition of the teat may be monitored by measuring electrical conductivity. Although reasonably easy to implement, this method typically offers poor detection performance.
Alternatively, the chemical composition of the milk may be analysed to measure SCC or lactate dehydrogenase levels. Chemical testing of milk may be economically practical at herd level with bulk milk sampling, but is extremely expensive and labour intensive to implement for individual animals.
Therefore, there remains a need for reliable automated identification of potential cases of diseases such as mastitis and/or or of other health and welfare conditions in dairy animal herds at an early stage, in a cost effective manner.
By dairy animals we mean animals used in agriculture for the production of milk for human consumption, including but not limited to dairy cows, goats, buffalo, sheep, horses and camels.